Big Data

High Costs Obstructing Your Data Plans? How Real-Time Access Removes Barriers to Data Unification

Enterprise data is expected to more than double by 2026, with cloud data storage growing by nearly 20% annually. In today’s data-driven economy, organizations are tasked with managing and extracting insights and generating value from vast amounts of enterprise data. But that’s easier said than done.

The high cost and complexity of data management are holding businesses back from achieving their digital ambitions. A staggering 93% of IT decision-makers say storage and data management complexities hinder their digital transformation efforts, while 56% of business leaders say managing data-operating costs is a major pain point.

Traditional approaches to data management, storage, and connectivity aren’t working. These barriers cause businesses to miss out on opportunities to streamline processes, reduce costs, and make data-driven decisions that could propel them ahead of competitors.

The Data Dam That’s Clogging Up Data Management

In today’s cloud environment, enterprise data is generated in different formats, structures, and locations across various applications and networks — a web of digital touchpoints that can make data integration a daunting task. The increased volume and complexity of enterprise data have led to ballooning costs for talent, computing, and storage infrastructure.

As a result, traditional integration processes are no longer enough. For example, ETL (Extract, Transform, Load) pipelines that automatically extract data from various sources, transform it to the desired format, and load it into a target system or data warehouse, cause significant delays and impacts on data quality that can result in stale, outdated, or inaccurate data information.

Data that are replicated, transferred, and stored take up significant cloud space and, more importantly, budget that could be better spent on digital improvements and innovations. More than two-thirds of organizations say data storage accounts for 25% of their total cloud costs, and nearly one-fourth said it costs more than half of their budget.

While cloud storage rates may appear reasonable, enterprises that generate massive amounts of data can face cost issues when moving, storing, and querying data. When these fees compound, they coalesce into a digital dam that clogs up even the best-intentioned data strategy.

Consider the consumer packaged goods (CPG) industry, which generates massive amounts of data encompassing everything from inventory to point-of-sale to supply chain data, as well as customer information from online interactions, loyalty programs, and various other touchpoints. Such a high volume of data generation quickly becomes cost prohibitive to efficiently store and query. The same problems pop up for retailers dealing with large, rapidly changing volumes of transactional data or enterprises that constantly update data on their human resources platforms and ERPs.

Organizations must find a way to unify their data without incurring exorbitant expenses or bogging down their cloud infrastructure. When enterprises empower users to access and analyze data without delays, they can turn information into meaningful insights that drive more informed decisions and, ultimately, more value for the business.

Three Strategies to Move Data Unification Forward Faster

How can your business streamline, simplify, and save costs on data unification?

Real-time data connectivity platforms allow businesses to assemble data from different sources in a single location, enabling direct access to data at its source. Rather than extensive data replication and movement, real-time connectivity relies on APIs to seamlessly connect various sources — an approach taken by more than half of organizations today.

As you work to remove barriers to data unification and deliver better business results, consider the following three strategies to leverage real-time connectivity platforms — and empower your organization to move forward in its digital journey.


1. Set Clearly Defined Goals for Data

More than two-thirds of companies struggle to realize tangible benefits from data — and that’s often the result of poorly defined goals and mismanaged strategy. A robust data strategy is rooted in clearly defined business objectives and specific use cases that help drive value, along with continuous monitoring, ongoing improvement, and agility to adapt as your business objectives evolve and new challenges arise.

As you build out your data unification strategy or goal, consider what data your organization collects, who needs access to it, how they will use it, and why it drives your business forward. With a clear vision in mind, you can build data integration processes aligned with your strategic objectives and measure your progress along the way.

2. Adopt Scalable Technology

Four in 10 IT decision-makers worry their IT infrastructure won’t be able to handle future data demands. As enterprise data expands, you need scalable platforms that can handle massive data volumes and offer immediate access to data without delays.

Look for real-time solutions that offer the widest breadth and depth of connections —  and allow your organization to efficiently integrate data from various sources even as your data operations grow and evolve.

3. Engage the Entire Organization

Building a data-driven business requires more than just the right digital tools — it takes every employee, team, and department working together.

From entry-level positions to the C-suite, you will need to engage all stakeholders and align the entire organization around your data strategy. In particular, it’s crucial to foster greater collaboration and communication between different business units, along with providing the necessary training and support for all employees to understand the tools at their disposal and apply data analytics to their everyday work.

Real-time connectivity eliminates the complexities, costs, and delays associated with traditional data storage and movement. But implementing this scalable technology requires a robust data strategy, the right infrastructure capabilities, and the alignment of your entire organization.

Breaking down the barriers blocking data integration unleashes the full power of your enterprise data — from streamlining processes and reducing costs to extracting valuable insights to inform data-driven decisions. Once you’ve eliminated these common hurdles, the coast is clear for you to fully focus on outpacing the competition.

About the author: Manish Patel is the Chief Product Officer at CData. Manish is responsible for defining CData’s strategic product vision and roadmap. He has over 15 years of product management experience growing packaged software and cloud-based offerings across multiple SaaS companies, including Tier1, Valassis Digital, and Ipreo. Manish holds a Bachelor’s from the University of Westminster and is Scaled Agile Framework (SAFe) certified.

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